Lead early-phase AI systems: Design and build AI-first user experiences from the ground up, pairing rapid experimentation with strong measurement loops to evaluate performance, relevance, safety, and cost in production.
Influence product direction: Bring an engineering-driven perspective to what we build, how we build it, and which tradeoffs are worth making at early stages—charting a multi-step path that turns quick wins into durable, scalable capabilities.
Design and build scalable AI systems: Once direction is validated, evolve prototypes into reliable, maintainable, and observable production systems, balancing iteration speed with long-term platform health.
Build AI-powered product experiences: Develop AI-assisted modeling and authoring workflows to accelerate plan design, data mapping, and explanation for customers.
Deliver retrieval-augmented insights: Implement contextual help, explainers, and policy Q&A grounded in customer data and system metadata using robust retrieval-augmented generation patterns.
Own guardrails and evaluation: Design and implement evaluation and safety primitives—including offline and online evals, telemetry, human-in-the-loop workflows, safety filters, and red-teaming—to ensure trustworthy AI behavior.
Create reusable AI platform components: Build shared infrastructure for prompt orchestration, hybrid retrieval, caching, tracing, evaluation, and cost/performance controls that enable teams to ship AI features safely and efficiently.
Raise the technical bar: Contribute to architecture, coding standards, testing strategy, and mentoring; promote best practices across AI systems, platform design, and production readiness.

Requirements

6+ years of software engineering experience shipping production systems in fast-moving environments, including significant ownership of architecture, technical direction, and quality.
Demonstrated success building AI-powered products or platforms in highly exploratory settings (0→1, greenfield initiatives, early AI features), where model choice, system design, and product experience evolved together.
Hands-on experience designing, building, and operating AI systems in production, including:
Integrating LLMs or other models into real user workflows
Designing AI-first or AI-assisted product experiences
Managing inference performance, latency, cost, and reliability
Building feedback loops to continuously improve model behavior
Experience implementing AI evaluation and guardrails, such as:
Offline and online evaluations
Safety filters, policy enforcement, and failure detection
Human-in-the-loop workflows and red-teaming
Telemetry, tracing, and model performance monitoring
Fluency in modern product and platform development, with hands-on experience in Python/Django, TypeScript/JavaScript, React, and PostgreSQL, and the ability to build both backend systems and AI-powered user experiences.
Strong systems and platform thinking, including APIs, data modeling, scalability, observability, and the unique operational challenges of AI-enabled systems.
Sound engineering judgment in AI contexts, balancing rapid experimentation with long-term durability, safety, and maintainability.
High comfort with ambiguity and technical decision-making, able to evaluate multiple AI approaches, articulate tradeoffs, and move work forward without perfect specifications.
Excellent communication skills and product sensibility, with the ability to collaborate deeply with product, design, and stakeholders to translate AI capabilities into real customer value.

Benefits

(US-ONLY) 100% of medical, dental, and vision covered including 75% for dependents
Flexible vacation days and quarterly mental health days so you can recharge
(US-ONLY) 401k plan to participate in and save towards the future
Newest Apple products to help you do your best work
Employee Resource Groups (ERGs) to support and celebrate the shared identities and life experiences of communities within CaptivateIQ. ERGs directly support our company-wide DEI goals as a space for developing and retaining diverse talent

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

AI systems designAI-powered product developmentLLM integrationinference performance managementAI evaluation implementationPythonDjangoTypeScriptJavaScriptPostgreSQL

Soft skills

engineering judgmentcommunication skillscollaborationproduct sensibilitycomfort with ambiguitytechnical decision-makingscalability thinkingobservability thinkingsafety awarenessmentoring